Introduction

You can allow conflicts to occur, but you need to detect them using an optimistic locking mechanism (e.g. logical clock, MVCC)

Because MVCC (Multi-Version Concurrency Control) is such a prevalent Concurrency Control technique (not only in relational database systems, in this article, I’m going to explain how it works.

What’s the goal

When the ACID transaction properties were first defined, Serializability was assumed. And to provide a Strict Serializable transaction outcome, the 2PL (Two-Phase Locking) mechanism was employed. When using 2PL, every read requires a shared lock acquisition, while a write operation requires taking an exclusive lock.

a shared lock blocks Writers, but it allows other Readers to acquire the same shared lock

an exclusive lock blocks both Readers and Writers concurring for the same lock

For this reason, database researchers have come up with a different Concurrency Control model which tries to reduce locking to a bare minimum so that:

Readers don’t block Writers

Writers don’t block Readers

The only use case that can still generate contention is when two concurrent transactions try to modify the same record since, once modified, a row is always locked until the transaction that modified this record either commits or rolls back.

In order to specify the aforementioned Reader/Writer non-locking behavior, the Concurrency Control mechanism must operate on multiple versions of the same record, hence this mechanism is called Multi-Version Concurrency Control (MVCC).

While 2PL is pretty much standard, there’s no standard MVCC implementation, each database taking a slightly different approach. In this article, we are going to use PostgreSQL since its MVCC implementation is the easiest one to visualize.

PostgreSQL

While Oracle and MySQL use the undo log to capture uncommitted changes so that rows can be reconstructed to their previously committed version, PostgreSQL stores all row versions in the table data structure.

What’s even more interesting is that every row has two additional columns:

– which defines the transaction id that inserted the record

– which defines the transaction id that deleted the row

In PostgreSQL, the Transaction Id is a 32-bit integer, and the VACUUM process is responsible (among other things like reclaiming old row versions that are no longer in use) for making sure that the id does not overflow.

If the transaction id is higher than the value of a committed row, the transaction is allowed to read this record version.

If the transaction id is lower than the value, then it’s up to the isolation level to decide if a record should be visible or not. For READ COMMITTED, the currently executing statement timestamp becomes the lower boundary for row visibility. For REPEATABLE READ or SERIALIZABLE, all reads are relative to the start timestamp of the currently running transaction.

Deleting a record

To understand how DELETE works in MVCC, consider the following diagram:

Both Alice and Bob start a new transaction, and we can see their transaction ids by calling the txid_current() PostgreSQL function

When Bob deletes a post row, the column value is set to Bob’s transaction id

Under default Read Committed isolation level, until Bob manages to commit his transaction, Alice can still see the record that was deleted by ob

After Bob has committed, Alice can no longer see the deleted row

While in 2PL, Bob’s modification would block Alice read statement, in MVCC Alice is still allowed to see the previous version until Bob manages to commit his transaction.

The DELETE operation does not physically remove a record, it just marks it as ready for deletion, and the VACUUM process will collect it when this row is no longer in use by any current running transaction.

If the transaction id is greater than the value of a committed row, the transaction is not allowed to read this record version anymore.

If the transaction id is lower than the value, then it’s up to the isolation level to decide if a record should be visible or not. For READ COMMITTED, the currently executing statement timestamp becomes the lower boundary for row visibility. For REPEATABLE READ or SERIALIZABLE, all reads are relative to the start timestamp of the currently running transaction.

Updating a record

To understand how UPDATE works in MVCC, consider the following diagram:

Both Alice and Bob start a new transaction, and we can see their transaction ids by calling the txid_current() PostgreSQL function

When Bob updates a post record, we can see two operations happening: a DELETE and an INSERT.
The previous row version is marked as deleted by setting the column value to Bob’s transaction id, and a new row version is created which has the column value set to Bob’s transaction id

Under default Read Committed isolation level, until Bob manages to commit his transaction, Alice can still see the previous record version

After Bob has committed, Alice can now see the new row version that was updated by Bob

If you enjoyed this article, I bet you are going to love my Book and Video Courses as well.

Conclusion

By allowing multiple versions of the same record, there is going to be less contention on reading/writing records since Readers will not block writers and Writers will not block Readers as well.